Pandas Profiling Report

Dataset statistics

Number of variables	24
Number of observations	99
Missing cells	50
Missing cells (%)	2.1%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	18.7 KiB
Average record size in memory	193.3 B

Variable types

Numeric	12
Categorical	12

Alerts

`city` has constant value "Lahore"	Constant
`province_name` has constant value "Punjab"	Constant
`purpose` has constant value "For Sale"	Constant
`page_url` has a high cardinality: 99 distinct values	High cardinality
`price` is highly correlated with `area_marla` and 1 other fields	High correlation
`longitude` is highly correlated with `day`	High correlation
`baths` is highly correlated with `bedrooms`	High correlation
`area_marla` is highly correlated with `price` and 1 other fields	High correlation
`area_sqft` is highly correlated with `price` and 1 other fields	High correlation
`bedrooms` is highly correlated with `baths`	High correlation
`day` is highly correlated with `longitude`	High correlation
`location_id` is highly correlated with `longitude` and 1 other fields	High correlation
`price` is highly correlated with `area_marla` and 1 other fields	High correlation
`latitude` is highly correlated with `longitude`	High correlation
`longitude` is highly correlated with `location_id` and 2 other fields	High correlation
`baths` is highly correlated with `bedrooms`	High correlation
`area_marla` is highly correlated with `price` and 1 other fields	High correlation
`area_sqft` is highly correlated with `price` and 1 other fields	High correlation
`bedrooms` is highly correlated with `baths`	High correlation
`year` is highly correlated with `month`	High correlation
`month` is highly correlated with `year`	High correlation
`day` is highly correlated with `location_id` and 1 other fields	High correlation
`price` is highly correlated with `area_marla` and 1 other fields	High correlation
`baths` is highly correlated with `bedrooms`	High correlation
`area_marla` is highly correlated with `price` and 1 other fields	High correlation
`area_sqft` is highly correlated with `price` and 1 other fields	High correlation
`bedrooms` is highly correlated with `baths`	High correlation
`location` is highly correlated with `locality` and 10 other fields	High correlation
`locality` is highly correlated with `location` and 10 other fields	High correlation
`agency` is highly correlated with `location` and 8 other fields	High correlation
`price_bin` is highly correlated with `location` and 8 other fields	High correlation
`area` is highly correlated with `location` and 7 other fields	High correlation
`property_type` is highly correlated with `location` and 6 other fields	High correlation
`city` is highly correlated with `location` and 10 other fields	High correlation
`purpose` is highly correlated with `location` and 10 other fields	High correlation
`province_name` is highly correlated with `location` and 10 other fields	High correlation
`agent` is highly correlated with `location` and 8 other fields	High correlation
`page_url` is highly correlated with `location` and 10 other fields	High correlation
`date_added` is highly correlated with `location` and 7 other fields	High correlation
`property_id` is highly correlated with `location_id` and 10 other fields	High correlation
`location_id` is highly correlated with `property_id` and 13 other fields	High correlation
`page_url` is highly correlated with `property_id` and 18 other fields	High correlation
`property_type` is highly correlated with `page_url` and 4 other fields	High correlation
`price` is highly correlated with `page_url` and 6 other fields	High correlation
`price_bin` is highly correlated with `location_id` and 10 other fields	High correlation
`location` is highly correlated with `property_id` and 18 other fields	High correlation
`locality` is highly correlated with `property_id` and 18 other fields	High correlation
`latitude` is highly correlated with `property_id` and 11 other fields	High correlation
`longitude` is highly correlated with `property_id` and 15 other fields	High correlation
`baths` is highly correlated with `location_id` and 14 other fields	High correlation
`area` is highly correlated with `property_id` and 18 other fields	High correlation
`area_marla` is highly correlated with `page_url` and 8 other fields	High correlation
`area_sqft` is highly correlated with `page_url` and 8 other fields	High correlation
`bedrooms` is highly correlated with `page_url` and 10 other fields	High correlation
`date_added` is highly correlated with `property_id` and 17 other fields	High correlation
`month` is highly correlated with `location_id` and 10 other fields	High correlation
`day` is highly correlated with `property_id` and 12 other fields	High correlation
`agency` is highly correlated with `property_id` and 16 other fields	High correlation
`agent` is highly correlated with `property_id` and 14 other fields	High correlation
`agency` has 25 (25.3%) missing values	Missing
`agent` has 25 (25.3%) missing values	Missing
`page_url` is uniformly distributed	Uniform
`property_id` has unique values	Unique
`page_url` has unique values	Unique
`baths` has 17 (17.2%) zeros	Zeros
`bedrooms` has 12 (12.1%) zeros	Zeros

Reproduction

Analysis started	2022-11-09 14:25:09.838781
Analysis finished	2022-11-09 14:25:39.179544
Duration	29.34 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

property_id
Real number (ℝ_≥0)

HIGH CORRELATION
UNIQUE

Distinct	99
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3272394.384

Minimum	347795
Maximum	5019310
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	920.0 B

Quantile statistics

Minimum	347795
5-th percentile	775459.1
Q1	2439780
median	3892037
Q3	4306236.5
95-th percentile	4684132.2
Maximum	5019310
Range	4671515
Interquartile range (IQR)	1866456.5

Descriptive statistics

Standard deviation	1252689.148
Coefficient of variation (CV)	0.3828050658
Kurtosis	-0.5529985553
Mean	3272394.384
Median Absolute Deviation (MAD)	649686
Skewness	-0.7291476877
Sum	323967044
Variance	1.5692301 × 10¹²
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
347795	1	1.0%
4307496	1	1.0%
4249571	1	1.0%
4170552	1	1.0%
4159826	1	1.0%
4153988	1	1.0%
4111694	1	1.0%
4107715	1	1.0%
4100382	1	1.0%
4034402	1	1.0%
Other values (89)	89	89.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
347795	1	1.0%
482892	1	1.0%
555962	1	1.0%
562843	1	1.0%
686990	1	1.0%
785289	1	1.0%
983065	1	1.0%
983066	1	1.0%
983075	1	1.0%
1286643	1	1.0%

Value	Count	Frequency (%)
5019310	1	1.0%
4951451	1	1.0%
4940629	1	1.0%
4907568	1	1.0%
4747413	1	1.0%
4677101	1	1.0%
4570988	1	1.0%
4560911	1	1.0%
4557799	1	1.0%
4536854	1	1.0%

location_id
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct	59
Distinct (%)	59.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5073.858586

Minimum	7
Maximum	10542
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	920.0 B

Quantile statistics

Minimum	7
5-th percentile	74.4
Q1	1695.5
median	3847
Q3	9433
95-th percentile	9436
Maximum	10542
Range	10535
Interquartile range (IQR)	7737.5

Descriptive statistics

Standard deviation	3659.481259
Coefficient of variation (CV)	0.721242265
Kurtosis	-1.591116522
Mean	5073.858586
Median Absolute Deviation (MAD)	3469
Skewness	0.1419269724
Sum	502312
Variance	13391803.08
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
9435	9	9.1%
9434	6	6.1%
9433	6	6.1%
8172	5	5.1%
9436	4	4.0%
9432	3	3.0%
10542	3	3.0%
1784	3	3.0%
514	3	3.0%
8	2	2.0%
Other values (49)	55	55.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
7	1	1.0%
8	2	2.0%
48	1	1.0%
69	1	1.0%
75	1	1.0%
154	2	2.0%
373	1	1.0%
377	1	1.0%
378	1	1.0%
496	1	1.0%

Value	Count	Frequency (%)
10542	3	3.0%
9747	1	1.0%
9436	4	4.0%
9435	9	9.1%
9434	6	6.1%
9433	6	6.1%
9432	3	3.0%
8444	1	1.0%
8425	1	1.0%
8172	5	5.1%

page_url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct	99
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	920.0 B

https://www.zameen.com/Property/lahore_model_town_6_kanal_excellent_house_for_sale_in_model_town-347795-8-1.html	1
https://www.zameen.com/Property/bahria_town_bahria_town_sector_c_vip_class_10_marla_brand_new_house_for_sale_in_bahria_town_lahore_in_sector_c-4307496-1784-1.html	1
https://www.zameen.com/Property/gulberg_gulberg_4_exclusive_location_house_for_sale-4249571-3847-1.html	1
https://www.zameen.com/Property/allama_iqbal_town_allama_iqbal_town_pak_block_2_marla_double_storey_house_for_sale-4170552-3527-1.html	1
https://www.zameen.com/Property/allama_iqbal_town_allama_iqbal_town_pak_block_2_marla_house_is_available_for_sale-4159826-3527-1.html	1
Other values (94)	94

Length

Max length	165
Median length	126
Mean length	125.2424242
Min length	88

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	99 ?
Unique (%)	100.0%

Sample

1st row	https://www.zameen.com/Property/lahore_model_town_6_kanal_excellent_house_for_sale_in_model_town-347795-8-1.html
2nd row	https://www.zameen.com/Property/lahore_multan_road_1_kanal_house_for_sale-482892-48-1.html
3rd row	https://www.zameen.com/Property/eden_eden_avenue_9_marla_house_for_sale-555962-75-1.html
4th row	https://www.zameen.com/Property/gulberg_2_gulberg_2_block_s_semi_commercial_house_for_sale_near_mm_alam_price_negotiable-562843-3821-1.html
5th row	https://www.zameen.com/Property/allama_iqbal_town_allama_iqbal_town_raza_block_11_marla_house_for_sale_at_best_location_with_noc_ready-686990-3522-1.html

Common Values

Value	Count	Frequency (%)
https://www.zameen.com/Property/lahore_model_town_6_kanal_excellent_house_for_sale_in_model_town-347795-8-1.html	1	1.0%
https://www.zameen.com/Property/bahria_town_bahria_town_sector_c_vip_class_10_marla_brand_new_house_for_sale_in_bahria_town_lahore_in_sector_c-4307496-1784-1.html	1	1.0%
https://www.zameen.com/Property/gulberg_gulberg_4_exclusive_location_house_for_sale-4249571-3847-1.html	1	1.0%
https://www.zameen.com/Property/allama_iqbal_town_allama_iqbal_town_pak_block_2_marla_double_storey_house_for_sale-4170552-3527-1.html	1	1.0%
https://www.zameen.com/Property/allama_iqbal_town_allama_iqbal_town_pak_block_2_marla_house_is_available_for_sale-4159826-3527-1.html	1	1.0%
https://www.zameen.com/Property/bahria_town_sector_c_bahria_town_tulip_block_10_marla_brand_new_house_in_sector_c_bahria_town_lahore-4153988-1789-1.html	1	1.0%
https://www.zameen.com/Property/dha_phase_5_dha_phase_5_block_a_1_kanal_beautiful_bungalow_house_for_sale-4111694-1598-1.html	1	1.0%
https://www.zameen.com/Property/dha_defence_dha_phase_6_1_kanal_brand_new_beautiful_bungalow_for_sale-4107715-1448-1.html	1	1.0%
https://www.zameen.com/Property/askari_10_askari_10_sector_f_17_marla_corner_brand_new_brig_house_available_for_sale-4100382-10542-1.html	1	1.0%
https://www.zameen.com/Property/lahore_samanabad_house_in_samanabad_for_sale-4034402-377-1.html	1	1.0%
Other values (89)	89	89.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
https://www.zameen.com/property/lahore_model_town_6_kanal_excellent_house_for_sale_in_model_town-347795-8-1.html	1	1.0%
https://www.zameen.com/property/askari_10_askari_10_sector_c_10_marla_haider_design_is_available_for_sale-2439785-9434-1.html	1	1.0%
https://www.zameen.com/property/eden_eden_avenue_9_marla_house_for_sale-555962-75-1.html	1	1.0%
https://www.zameen.com/property/gulberg_2_gulberg_2_block_s_semi_commercial_house_for_sale_near_mm_alam_price_negotiable-562843-3821-1.html	1	1.0%
https://www.zameen.com/property/allama_iqbal_town_allama_iqbal_town_raza_block_11_marla_house_for_sale_at_best_location_with_noc_ready-686990-3522-1.html	1	1.0%
https://www.zameen.com/property/gulberg_paf_falcon_complex_matz_service_offer_1_kanal_house_for_sale-785289-3102-1.html	1	1.0%
https://www.zameen.com/property/eme_society_eme_society_block_e_house_for_sale-983065-3749-1.html	1	1.0%
https://www.zameen.com/property/eme_society_eme_society_block_a_house_for_sale-983066-3745-1.html	1	1.0%
https://www.zameen.com/property/izmir_town_izmir_town_block_q_house_for_sale-983075-3931-1.html	1	1.0%
https://www.zameen.com/property/eden_eden_palace_villas_7_5_marla_luxury_house_is_available_for_sale-1286643-3733-1.html	1	1.0%
Other values (89)	89	89.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

property_type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	920.0 B

House	97
Flat	2

Length

Max length	5
Median length	5
Mean length	4.97979798
Min length	4

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	House
2nd row	House
3rd row	House
4th row	House
5th row	House

Common Values

Value	Count	Frequency (%)
House	97	98.0%
Flat	2	2.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
house	97	98.0%
flat	2	2.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

price
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	66
Distinct (%)	66.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	77047474.75

Minimum	3200000
Maximum	1250000000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	920.0 B

Quantile statistics

Minimum	3200000
5-th percentile	7530000
Q1	20750000
median	23500000
Q3	49750000
95-th percentile	362000000
Maximum	1250000000
Range	1246800000
Interquartile range (IQR)	29000000

Descriptive statistics

Standard deviation	189835518.7
Coefficient of variation (CV)	2.46387723
Kurtosis	27.08201053
Mean	77047474.75
Median Absolute Deviation (MAD)	11500000
Skewness	5.02013655
Sum	7627700000
Variance	3.603752415 × 10¹⁶
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
40000000	5	5.1%
23000000	5	5.1%
22500000	5	5.1%
21500000	4	4.0%
23500000	4	4.0%
22000000	3	3.0%
50000000	3	3.0%
35000000	3	3.0%
21000000	3	3.0%
17500000	2	2.0%
Other values (56)	62	62.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
3200000	2	2.0%
5500000	2	2.0%
6000000	1	1.0%
7700000	1	1.0%
8000000	1	1.0%
8500000	1	1.0%
9500000	1	1.0%
11800000	1	1.0%
12000000	2	2.0%
12500000	1	1.0%

Value	Count	Frequency (%)
1250000000	1	1.0%
1200000000	1	1.0%
620000000	1	1.0%
480000000	1	1.0%
380000000	1	1.0%
360000000	1	1.0%
220000000	1	1.0%
180000000	1	1.0%
160000000	1	1.0%
125000000	1	1.0%

price_bin
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	4.0%
Missing	0
Missing (%)	0.0%
Memory size	920.0 B

Very High	43
High	41
Low	9
Medium	6

Length

Max length	9
Median length	4
Mean length	6.202020202
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Very High
2nd row	Very High
3rd row	Low
4th row	Very High
5th row	High

Common Values

Value	Count	Frequency (%)
Very High	43	43.4%
High	41	41.4%
Low	9	9.1%
Medium	6	6.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
high	84	59.2%
very	43	30.3%
low	9	6.3%
medium	6	4.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

location
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	30
Distinct (%)	30.3%
Missing	0
Missing (%)	0.0%
Memory size	920.0 B

Askari	31
Gulberg	13
DHA Defence	10
Bahria Town	6
EME Society	5
Other values (25)	34

Length

Max length	36
Median length	9
Mean length	9.575757576
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	19 ?
Unique (%)	19.2%

Sample

1st row	Model Town
2nd row	Multan Road
3rd row	Eden
4th row	Gulberg
5th row	Allama Iqbal Town

Common Values

Value	Count	Frequency (%)
Askari	31	31.3%
Gulberg	13	13.1%
DHA Defence	10	10.1%
Bahria Town	6	6.1%
EME Society	5	5.1%
Allama Iqbal Town	4	4.0%
Upper Mall	3	3.0%
Valencia Housing Society	2	2.0%
Paragon City	2	2.0%
Model Town	2	2.0%
Other values (20)	21	21.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
askari	31	19.6%
town	16	10.1%
gulberg	13	8.2%
dha	10	6.3%
defence	10	6.3%
society	8	5.1%
bahria	6	3.8%
eme	5	3.2%
allama	4	2.5%
iqbal	4	2.5%
Other values (35)	51	32.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

city
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Memory size	920.0 B

Lahore	99

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Lahore
2nd row	Lahore
3rd row	Lahore
4th row	Lahore
5th row	Lahore

Common Values

Value	Count	Frequency (%)
Lahore	99	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
lahore	99	100.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

province_name
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Memory size	920.0 B

Punjab	99

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Punjab
2nd row	Punjab
3rd row	Punjab
4th row	Punjab
5th row	Punjab

Common Values

Value	Count	Frequency (%)
Punjab	99	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
punjab	99	100.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

locality
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	30
Distinct (%)	30.3%
Missing	0
Missing (%)	0.0%
Memory size	920.0 B

Askari, Lahore, Punjab	31
Gulberg, Lahore, Punjab	13
DHA Defence, Lahore, Punjab	10
Bahria Town, Lahore, Punjab	6
EME Society, Lahore, Punjab	5
Other values (25)	34

Length

Max length	52
Median length	25
Mean length	25.57575758
Min length	19

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	19 ?
Unique (%)	19.2%

Sample

1st row	Model Town, Lahore, Punjab
2nd row	Multan Road, Lahore, Punjab
3rd row	Eden, Lahore, Punjab
4th row	Gulberg, Lahore, Punjab
5th row	Allama Iqbal Town, Lahore, Punjab

Common Values

Value	Count	Frequency (%)
Askari, Lahore, Punjab	31	31.3%
Gulberg, Lahore, Punjab	13	13.1%
DHA Defence, Lahore, Punjab	10	10.1%
Bahria Town, Lahore, Punjab	6	6.1%
EME Society, Lahore, Punjab	5	5.1%
Allama Iqbal Town, Lahore, Punjab	4	4.0%
Upper Mall, Lahore, Punjab	3	3.0%
Valencia Housing Society, Lahore, Punjab	2	2.0%
Paragon City, Lahore, Punjab	2	2.0%
Model Town, Lahore, Punjab	2	2.0%
Other values (20)	21	21.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
lahore	99	27.8%
punjab	99	27.8%
askari	31	8.7%
town	16	4.5%
gulberg	13	3.7%
dha	10	2.8%
defence	10	2.8%
society	8	2.2%
bahria	6	1.7%
eme	5	1.4%
Other values (37)	59	16.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

latitude
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct	61
Distinct (%)	61.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	31.50025706

Minimum	31.37108
Maximum	31.71727872
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	920.0 B

Quantile statistics

Minimum	31.37108
5-th percentile	31.3809768
Q1	31.466227
median	31.521776
Q3	31.536068
95-th percentile	31.5528568
Maximum	31.71727872
Range	0.3461987155
Interquartile range (IQR)	0.069841

Descriptive statistics

Standard deviation	0.05707246082
Coefficient of variation (CV)	0.001811809367
Kurtosis	1.504098145
Mean	31.50025706
Median Absolute Deviation (MAD)	0.020338
Skewness	-0.2038244183
Sum	3118.525449
Variance	0.003257265784
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
31.533161	8	8.1%
31.537458	6	6.1%
31.53327	5	5.1%
31.469155	5	5.1%
31.536068	4	4.0%
31.537239	3	3.0%
31.542114	3	3.0%
31.533849	3	3.0%
31.374195	3	3.0%
31.437744	2	2.0%
Other values (51)	57	57.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
31.37108	1	1.0%
31.374195	3	3.0%
31.374414	1	1.0%
31.381706	1	1.0%
31.400096	1	1.0%
31.402513	1	1.0%
31.40537	1	1.0%
31.409106	1	1.0%
31.431593	1	1.0%
31.434668	1	1.0%

Value	Count	Frequency (%)
31.71727872	1	1.0%
31.597234	1	1.0%
31.590234	1	1.0%
31.57443055	1	1.0%
31.567912	1	1.0%
31.551184	1	1.0%
31.54913521	1	1.0%
31.543431	1	1.0%
31.542114	3	3.0%
31.539206	1	1.0%

longitude
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	62
Distinct (%)	62.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	74.35381822

Minimum	74.177749
Maximum	74.474513
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	920.0 B

Quantile statistics

Minimum	74.177749
5-th percentile	74.191482
Q1	74.29842
median	74.355898
Q3	74.41822
95-th percentile	74.470553
Maximum	74.474513
Range	0.296764
Interquartile range (IQR)	0.1198

Descriptive statistics

Standard deviation	0.08504638763
Coefficient of variation (CV)	0.001143806595
Kurtosis	-0.663607522
Mean	74.35381822
Median Absolute Deviation (MAD)	0.058036
Skewness	-0.6767585732
Sum	7361.028004
Variance	0.007232888048
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
74.419481	8	8.1%
74.413323	6	6.1%
74.470553	5	5.1%
74.41358	5	5.1%
74.408666	4	4.0%
74.355898	3	3.0%
74.409633	3	3.0%
74.420211	3	3.0%
74.191482	3	3.0%
74.348202	2	2.0%
Other values (52)	57	57.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
74.177749	1	1.0%
74.17998	1	1.0%
74.181662	1	1.0%
74.190316	1	1.0%
74.191482	3	3.0%
74.195294	1	1.0%
74.200931	1	1.0%
74.209685	2	2.0%
74.21349	2	2.0%
74.214005	1	1.0%

Value	Count	Frequency (%)
74.474513	1	1.0%
74.470553	5	5.1%
74.456184	1	1.0%
74.45599191	1	1.0%
74.451342	1	1.0%
74.445906	1	1.0%
74.44369633	1	1.0%
74.440012	1	1.0%
74.429569	1	1.0%
74.427137	1	1.0%

baths
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	8
Distinct (%)	8.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.313131313

Minimum	0
Maximum	8
Zeros	17
Zeros (%)	17.2%
Negative	0
Negative (%)	0.0%
Memory size	920.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	3.5
median	5
Q3	6
95-th percentile	7
Maximum	8
Range	8
Interquartile range (IQR)	2.5

Descriptive statistics

Standard deviation	2.319599124
Coefficient of variation (CV)	0.5377993285
Kurtosis	-0.3894685051
Mean	4.313131313
Median Absolute Deviation (MAD)	1
Skewness	-0.8205742852
Sum	427
Variance	5.380540095
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
5	28	28.3%
6	22	22.2%
0	17	17.2%
4	12	12.1%
7	9	9.1%
3	4	4.0%
2	4	4.0%
8	3	3.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	17	17.2%
2	4	4.0%
3	4	4.0%
4	12	12.1%
5	28	28.3%
6	22	22.2%
7	9	9.1%
8	3	3.0%

Value	Count	Frequency (%)
8	3	3.0%
7	9	9.1%
6	22	22.2%
5	28	28.3%
4	12	12.1%
3	4	4.0%
2	4	4.0%
0	17	17.2%

area
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	30
Distinct (%)	30.3%
Missing	0
Missing (%)	0.0%
Memory size	920.0 B

10 Marla	33
1 Kanal	22
2 Kanal	5
3 Marla	3
12 Marla	3
Other values (25)	33

Length

Max length	9
Median length	8
Mean length	7.676767677
Min length	7

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	18 ?
Unique (%)	18.2%

Sample

1st row	6 Kanal
2nd row	1 Kanal
3rd row	9 Marla
4th row	1 Kanal
5th row	11 Marla

Common Values

Value	Count	Frequency (%)
10 Marla	33	33.3%
1 Kanal	22	22.2%
2 Kanal	5	5.1%
3 Marla	3	3.0%
12 Marla	3	3.0%
17 Marla	3	3.0%
2 Marla	2	2.0%
5 Marla	2	2.0%
11 Marla	2	2.0%
8 Kanal	2	2.0%
Other values (20)	22	22.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
marla	61	30.8%
kanal	38	19.2%
10	34	17.2%
1	22	11.1%
2	7	3.5%
17	3	1.5%
8	3	1.5%
12	3	1.5%
3	3	1.5%
5	2	1.0%
Other values (17)	22	11.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

area_marla
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	30
Distinct (%)	30.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	22.86262626

Minimum	2
Maximum	200
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	920.0 B

Quantile statistics

Minimum	2
5-th percentile	3
Q1	10
median	10
Q3	20
95-th percentile	96.6
Maximum	200
Range	198
Interquartile range (IQR)	10

Descriptive statistics

Standard deviation	33.74980147
Coefficient of variation (CV)	1.476199675
Kurtosis	13.22936034
Mean	22.86262626
Median Absolute Deviation (MAD)	6
Skewness	3.591827445
Sum	2263.4
Variance	1139.049099
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=30)

Value	Count	Frequency (%)
10	33	33.3%
20	22	22.2%
40	5	5.1%
3	3	3.0%
12	3	3.0%
17	3	3.0%
2	2	2.0%
5	2	2.0%
11	2	2.0%
160	2	2.0%
Other values (20)	22	22.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2	2	2.0%
2.5	1	1.0%
3	3	3.0%
4	1	1.0%
5	2	2.0%
5.5	1	1.0%
6	1	1.0%
7	1	1.0%
7.5	1	1.0%
8	1	1.0%

Value	Count	Frequency (%)
200	1	1.0%
160	2	2.0%
130	1	1.0%
120	1	1.0%
94	1	1.0%
80	1	1.0%
40	5	5.1%
32	1	1.0%
24	1	1.0%
22	2	2.0%

area_sqft
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	30
Distinct (%)	30.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6224.372525

Minimum	544.5
Maximum	54450.2
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	920.0 B

Quantile statistics

Minimum	544.5
5-th percentile	816.75
Q1	2722.51
median	2722.51
Q3	5445.02
95-th percentile	26299.443
Maximum	54450.2
Range	53905.7
Interquartile range (IQR)	2722.51

Descriptive statistics

Standard deviation	9188.417241
Coefficient of variation (CV)	1.476199762
Kurtosis	13.22936044
Mean	6224.372525
Median Absolute Deviation (MAD)	1633.51
Skewness	3.591827422
Sum	616212.88
Variance	84427011.4
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=30)

Value	Count	Frequency (%)
2722.51	33	33.3%
5445.02	22	22.2%
10890.04	5	5.1%
816.75	3	3.0%
3267.01	3	3.0%
4628.27	3	3.0%
544.5	2	2.0%
1361.25	2	2.0%
2994.76	2	2.0%
43560.16	2	2.0%
Other values (20)	22	22.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
544.5	2	2.0%
680.63	1	1.0%
816.75	3	3.0%
1089	1	1.0%
1361.25	2	2.0%
1497.38	1	1.0%
1633.51	1	1.0%
1905.76	1	1.0%
2041.88	1	1.0%
2178.01	1	1.0%

Value	Count	Frequency (%)
54450.2	1	1.0%
43560.16	2	2.0%
35392.63	1	1.0%
32670.12	1	1.0%
25591.59	1	1.0%
21780.08	1	1.0%
10890.04	5	5.1%
8712.03	1	1.0%
6534.02	1	1.0%
5989.52	2	2.0%

purpose
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Memory size	920.0 B

For Sale	99

Length

Max length	8
Median length	8
Mean length	8
Min length	8

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	For Sale
2nd row	For Sale
3rd row	For Sale
4th row	For Sale
5th row	For Sale

Common Values

Value	Count	Frequency (%)
For Sale	99	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
for	99	50.0%
sale	99	50.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

bedrooms
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	7
Distinct (%)	7.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.01010101

Minimum	0
Maximum	8
Zeros	12
Zeros (%)	12.1%
Negative	0
Negative (%)	0.0%
Memory size	920.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	3.5
median	4
Q3	5
95-th percentile	6
Maximum	8
Range	8
Interquartile range (IQR)	1.5

Descriptive statistics

Standard deviation	1.854365778
Coefficient of variation (CV)	0.4624237079
Kurtosis	0.6904686535
Mean	4.01010101
Median Absolute Deviation (MAD)	1
Skewness	-0.818601548
Sum	397
Variance	3.438672439
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
5	31	31.3%
4	29	29.3%
0	12	12.1%
6	11	11.1%
3	10	10.1%
8	3	3.0%
2	3	3.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	12	12.1%
2	3	3.0%
3	10	10.1%
4	29	29.3%
5	31	31.3%
6	11	11.1%
8	3	3.0%

Value	Count	Frequency (%)
8	3	3.0%
6	11	11.1%
5	31	31.3%
4	29	29.3%
3	10	10.1%
2	3	3.0%
0	12	12.1%

date_added
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	23
Distinct (%)	23.2%
Missing	0
Missing (%)	0.0%
Memory size	920.0 B

06-18-2019	32
07-03-2019	11
05-03-2019	10
04-04-2019	9
06-25-2019	7
Other values (18)	30

Length

Max length	10
Median length	10
Mean length	10
Min length	10

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	12 ?
Unique (%)	12.1%

Sample

1st row	07-17-2019
2nd row	10-06-2018
3rd row	07-03-2019
4th row	04-04-2019
5th row	04-04-2019

Common Values

Value	Count	Frequency (%)
06-18-2019	32	32.3%
07-03-2019	11	11.1%
05-03-2019	10	10.1%
04-04-2019	9	9.1%
06-25-2019	7	7.1%
04-03-2019	6	6.1%
06-11-2019	3	3.0%
02-03-2019	3	3.0%
06-02-2019	2	2.0%
06-30-2019	2	2.0%
Other values (13)	14	14.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
06-18-2019	32	32.3%
07-03-2019	11	11.1%
05-03-2019	10	10.1%
04-04-2019	9	9.1%
06-25-2019	7	7.1%
04-03-2019	6	6.1%
06-11-2019	3	3.0%
02-03-2019	3	3.0%
06-02-2019	2	2.0%
06-30-2019	2	2.0%
Other values (13)	14	14.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

year
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2018.959596

Minimum	2018
Maximum	2019
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	920.0 B

Quantile statistics

Minimum	2018
5-th percentile	2019
Q1	2019
median	2019
Q3	2019
95-th percentile	2019
Maximum	2019
Range	1
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.1979070035
Coefficient of variation (CV)	9.802425163 × 10^-5
Kurtosis	20.89246473
Mean	2018.959596
Median Absolute Deviation (MAD)	0
Skewness	-4.740329111
Sum	199877
Variance	0.03916718202
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=2)

Value	Count	Frequency (%)
2019	95	96.0%
2018	4	4.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2018	4	4.0%
2019	95	96.0%

Value	Count	Frequency (%)
2019	95	96.0%
2018	4	4.0%

month
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct	10
Distinct (%)	10.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.666666667

Minimum	1
Maximum	12
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	920.0 B

Quantile statistics

Minimum	1
5-th percentile	2
Q1	5
median	6
Q3	6
95-th percentile	7
Maximum	12
Range	11
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.778557085
Coefficient of variation (CV)	0.3138630151
Kurtosis	3.700743963
Mean	5.666666667
Median Absolute Deviation (MAD)	1
Skewness	0.5306536478
Sum	561
Variance	3.163265306
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
6	48	48.5%
7	15	15.2%
4	15	15.2%
5	10	10.1%
2	4	4.0%
1	2	2.0%
12	2	2.0%
10	1	1.0%
3	1	1.0%
11	1	1.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	2	2.0%
2	4	4.0%
3	1	1.0%
4	15	15.2%
5	10	10.1%
6	48	48.5%
7	15	15.2%
10	1	1.0%
11	1	1.0%
12	2	2.0%

Value	Count	Frequency (%)
12	2	2.0%
11	1	1.0%
10	1	1.0%
7	15	15.2%
6	48	48.5%
5	10	10.1%
4	15	15.2%
3	1	1.0%
2	4	4.0%
1	2	2.0%

day
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	15
Distinct (%)	15.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	11.25252525

Minimum	1
Maximum	30
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	920.0 B

Quantile statistics

Minimum	1
5-th percentile	3
Q1	3
median	10
Q3	18
95-th percentile	25
Maximum	30
Range	29
Interquartile range (IQR)	15

Descriptive statistics

Standard deviation	8.438666393
Coefficient of variation (CV)	0.7499353437
Kurtosis	-1.319764034
Mean	11.25252525
Median Absolute Deviation (MAD)	7
Skewness	0.3691181431
Sum	1114
Variance	71.2110905
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=15)

Value	Count	Frequency (%)
18	33	33.3%
3	30	30.3%
4	11	11.1%
25	7	7.1%
5	4	4.0%
11	3	3.0%
2	2	2.0%
30	2	2.0%
17	1	1.0%
6	1	1.0%
Other values (5)	5	5.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	1	1.0%
2	2	2.0%
3	30	30.3%
4	11	11.1%
5	4	4.0%
6	1	1.0%
10	1	1.0%
11	3	3.0%
12	1	1.0%
17	1	1.0%

Value	Count	Frequency (%)
30	2	2.0%
26	1	1.0%
25	7	7.1%
22	1	1.0%
18	33	33.3%
17	1	1.0%
12	1	1.0%
11	3	3.0%
10	1	1.0%
6	1	1.0%

agency
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	16
Distinct (%)	21.6%
Missing	25
Missing (%)	25.3%
Memory size	920.0 B

Forces Properties	31
Punjaab Estates	12
Vital Estate	9
Hamza Real Estate	7
Sukhera Estate & Builders	3
Other values (11)	12

Length

Max length	28
Median length	17
Mean length	16.32432432
Min length	11

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	10 ?
Unique (%)	13.5%

Sample

1st row	Real Biz International
2nd row	Khan Estate
3rd row	Shahum Estate 2
4th row	MATZ Services
5th row	Sukhera Estate & Builders

Common Values

Value	Count	Frequency (%)
Forces Properties	31	31.3%
Punjaab Estates	12	12.1%
Vital Estate	9	9.1%
Hamza Real Estate	7	7.1%
Sukhera Estate & Builders	3	3.0%
Valo Marketing	2	2.0%
Real Biz International	1	1.0%
Rana Estate Agency	1	1.0%
The Property Lounge	1	1.0%
Jinnah Associates	1	1.0%
Other values (6)	6	6.1%
(Missing)	25	25.3%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
forces	31	18.5%
properties	31	18.5%
estate	24	14.3%
punjaab	12	7.1%
estates	12	7.1%
vital	9	5.4%
real	9	5.4%
hamza	7	4.2%
	4	2.4%
builders	4	2.4%
Other values (19)	25	14.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

agent
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	17
Distinct (%)	23.0%
Missing	25
Missing (%)	25.3%
Memory size	920.0 B

Khalid Saeed Khan	31
Irfan Rehman Khan	12
Shahbaz Mughal	9
Imran Shahad	7
Ahmed Sheraz Sukhera	3
Other values (12)	12

Length

Max length	45
Median length	17
Mean length	16.7972973
Min length	10

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	12 ?
Unique (%)	16.2%

Sample

1st row	Usama Khan
2nd row	mohsinkhan and B
3rd row	Babar Hameed, Raja Omar
4th row	Group Captain (R) Tajammul Baig
5th row	Ahmed Sheraz Sukhera

Common Values

Value	Count	Frequency (%)
Khalid Saeed Khan	31	31.3%
Irfan Rehman Khan	12	12.1%
Shahbaz Mughal	9	9.1%
Imran Shahad	7	7.1%
Ahmed Sheraz Sukhera	3	3.0%
Nabeel Khalid Ch M Naveed Muhammad Bin Shahid	1	1.0%
Rana Junaid	1	1.0%
Najam Ul Saqib	1	1.0%
Nabeel Khalid Muhammad Bin Shahid	1	1.0%
Shafiq Malik	1	1.0%
Other values (7)	7	7.1%
(Missing)	25	25.3%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
khan	44	20.8%
khalid	33	15.6%
saeed	31	14.6%
irfan	12	5.7%
rehman	12	5.7%
shahbaz	9	4.2%
mughal	9	4.2%
imran	7	3.3%
shahad	7	3.3%
ahmed	3	1.4%
Other values (35)	45	21.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	property_id	location_id	page_url	property_type	price	price_bin	location	city	province_name	locality	latitude	longitude	baths	area	area_marla	area_sqft	purpose	bedrooms	date_added	year	month	day	agency	agent
0	347795	8	https://www.zameen.com/Property/lahore_model_town_6_kanal_excellent_house_for_sale_in_model_town-347795-8-1.html	House	220000000	Very High	Model Town	Lahore	Punjab	Model Town, Lahore, Punjab	31.483869	74.325686	0	6 Kanal	120.0	32670.12	For Sale	0	07-17-2019	2019	7	17	Real Biz International	Usama Khan
1	482892	48	https://www.zameen.com/Property/lahore_multan_road_1_kanal_house_for_sale-482892-48-1.html	House	40000000	Very High	Multan Road	Lahore	Punjab	Multan Road, Lahore, Punjab	31.431593	74.179980	5	1 Kanal	20.0	5445.02	For Sale	5	10-06-2018	2018	10	6	Khan Estate	mohsinkhan and B
2	555962	75	https://www.zameen.com/Property/eden_eden_avenue_9_marla_house_for_sale-555962-75-1.html	House	9500000	Low	Eden	Lahore	Punjab	Eden, Lahore, Punjab	31.499348	74.416959	0	9 Marla	9.0	2450.26	For Sale	3	07-03-2019	2019	7	3	Shahum Estate 2	Babar Hameed, Raja Omar
3	562843	3821	https://www.zameen.com/Property/gulberg_2_gulberg_2_block_s_semi_commercial_house_for_sale_near_mm_alam_price_negotiable-562843-3821-1.html	House	125000000	Very High	Gulberg	Lahore	Punjab	Gulberg, Lahore, Punjab	31.522069	74.355512	7	1 Kanal	20.0	5445.02	For Sale	8	04-04-2019	2019	4	4	NaN	NaN
4	686990	3522	https://www.zameen.com/Property/allama_iqbal_town_allama_iqbal_town_raza_block_11_marla_house_for_sale_at_best_location_with_noc_ready-686990-3522-1.html	House	21000000	High	Allama Iqbal Town	Lahore	Punjab	Allama Iqbal Town, Lahore, Punjab	31.506483	74.286017	5	11 Marla	11.0	2994.76	For Sale	6	04-04-2019	2019	4	4	NaN	NaN
5	785289	3102	https://www.zameen.com/Property/gulberg_paf_falcon_complex_matz_service_offer_1_kanal_house_for_sale-785289-3102-1.html	House	52000000	Very High	Gulberg	Lahore	Punjab	Gulberg, Lahore, Punjab	31.495909	74.350569	6	1 Kanal	20.0	5445.02	For Sale	5	06-02-2019	2019	6	2	MATZ Services	Group Captain (R) Tajammul Baig
6	983065	3749	https://www.zameen.com/Property/eme_society_eme_society_block_e_house_for_sale-983065-3749-1.html	House	32500000	High	EME Society	Lahore	Punjab	EME Society, Lahore, Punjab	31.439978	74.209685	0	1 Kanal	20.0	5445.02	For Sale	5	07-03-2019	2019	7	3	Sukhera Estate & Builders	Ahmed Sheraz Sukhera
7	983066	3745	https://www.zameen.com/Property/eme_society_eme_society_block_a_house_for_sale-983066-3745-1.html	House	31500000	High	EME Society	Lahore	Punjab	EME Society, Lahore, Punjab	31.437744	74.213490	0	1 Kanal	20.0	5445.02	For Sale	6	07-03-2019	2019	7	3	Sukhera Estate & Builders	Ahmed Sheraz Sukhera
8	983075	3931	https://www.zameen.com/Property/izmir_town_izmir_town_block_q_house_for_sale-983075-3931-1.html	House	40000000	Very High	Izmir Town	Lahore	Punjab	Izmir Town, Lahore, Punjab	31.409106	74.181662	0	1.6 Kanal	32.0	8712.03	For Sale	6	07-03-2019	2019	7	3	Sukhera Estate & Builders	Ahmed Sheraz Sukhera
9	1286643	3733	https://www.zameen.com/Property/eden_eden_palace_villas_7_5_marla_luxury_house_is_available_for_sale-1286643-3733-1.html	House	13500000	Medium	Eden	Lahore	Punjab	Eden, Lahore, Punjab	31.441113	74.239683	4	7.5 Marla	7.5	2041.88	For Sale	4	04-04-2019	2019	4	4	NaN	NaN

Last rows

	property_id	location_id	page_url	property_type	price	price_bin	location	city	province_name	locality	latitude	longitude	baths	area	area_marla	area_sqft	purpose	bedrooms	date_added	year	month	day	agency	agent
89	4536854	3852	https://www.zameen.com/Property/gulberg_main_boulevard_gulberg_commercialized_piece_of_property_house_for_sale-4536854-3852-1.html	House	1200000000	Very High	Gulberg	Lahore	Punjab	Gulberg, Lahore, Punjab	31.519435	74.345548	0	8 Kanal	160.0	43560.16	For Sale	0	04-04-2019	2019	4	4	Punjaab Estates	Irfan Rehman Khan
90	4557799	3850	https://www.zameen.com/Property/gulberg_mm_alam_road_shopping_paradise_of_lahore_house_for_sale-4557799-3850-1.html	House	380000000	Very High	Gulberg	Lahore	Punjab	Gulberg, Lahore, Punjab	31.510471	74.350526	0	2 Kanal	40.0	10890.04	For Sale	0	05-03-2019	2019	5	3	Punjaab Estates	Irfan Rehman Khan
91	4560911	496	https://www.zameen.com/Property/mozang_mozang_chungi_al_qader_center_ground_floor_new_apartment_for_sale-4560911-496-1.html	Flat	3200000	Low	Mozang	Lahore	Punjab	Mozang, Lahore, Punjab	31.549135	74.315117	2	3 Marla	3.0	816.75	For Sale	2	07-03-2019	2019	7	3	NaN	NaN
92	4570988	1447	https://www.zameen.com/Property/dha_defence_dha_phase_5_original_faisal_rasool_brand_new_classical_bungalow-4570988-1447-1.html	House	59800000	Very High	DHA Defence	Lahore	Punjab	DHA Defence, Lahore, Punjab	31.462493	74.409342	7	1 Kanal	20.0	5445.02	For Sale	6	05-03-2019	2019	5	3	Harum Real Estate & Builders	Tayyab Khurshad
93	4677101	8172	https://www.zameen.com/Property/dha_defence_defence_raya_dha_raya_2_kanal_facing_golf_course_fully_basement_house_for_sale-4677101-8172-1.html	House	66000000	Very High	DHA Defence	Lahore	Punjab	DHA Defence, Lahore, Punjab	31.469155	74.470553	6	2 Kanal	40.0	10890.04	For Sale	6	06-25-2019	2019	6	25	Vital Estate	Shahbaz Mughal
94	4747413	154	https://www.zameen.com/Property/gulberg_zafar_ali_road_6_kanal_house_for_sale_on_zafar_ali_road_mall_road_upper_mall_lahore_excellent_location-4747413-154-1.html	House	360000000	Very High	Gulberg	Lahore	Punjab	Gulberg, Lahore, Punjab	31.538420	74.352357	7	10 Kanal	200.0	54450.20	For Sale	5	06-30-2019	2019	6	30	Hamza Real Estate	Imran Shahad
95	4907568	514	https://www.zameen.com/Property/lahore_upper_mall_4_kanal__house_for_sale_upper_mall_lahore-4907568-514-1.html	House	160000000	Very High	Upper Mall	Lahore	Punjab	Upper Mall, Lahore, Punjab	31.542114	74.355898	6	1 Kanal	20.0	5445.02	For Sale	5	01-18-2019	2019	1	18	Hamza Real Estate	Imran Shahad
96	4940629	8	https://www.zameen.com/Property/lahore_model_town_3_marla_house_for_sale-4940629-8-1.html	House	8000000	Low	Model Town	Lahore	Punjab	Model Town, Lahore, Punjab	31.473884	74.329080	3	3 Marla	3.0	816.75	For Sale	2	07-03-2019	2019	7	3	NaN	NaN
97	4951451	7	https://www.zameen.com/Property/lahore_gulberg_blue_zone_house_for_sale-4951451-7-1.html	House	480000000	Very High	Gulberg	Lahore	Punjab	Gulberg, Lahore, Punjab	31.522361	74.347172	0	4 Kanal	80.0	21780.08	For Sale	0	05-03-2019	2019	5	3	Punjaab Estates	Irfan Rehman Khan
98	5019310	1534	https://www.zameen.com/Property/garden_town_garden_town_ahmed_block_purely_residential_apartments_for_sale-5019310-1534-1.html	Flat	22500000	Very High	Garden Town	Lahore	Punjab	Garden Town, Lahore, Punjab	31.507800	74.318733	0	7 Marla	7.0	1905.76	For Sale	0	04-03-2019	2019	4	3	Punjaab Estates	Irfan Rehman Khan

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length